In laser processing, the intensity distribution of the laser beam affects the crater formation and the distribution of ablated particles ejection. In this study, we demonstrated the ejection control of semiconductor microdroplets such as the droplet size and ejection direction by irradiation of the target substrate using a ring-shaped pulsed laser. In addition, we demonstrated the suppression of spatter generation in laser welding of metals with support from the ring-shaped beam.
In recent years, laser welding has been widely used as an alternative to arc welding because of its high power and faster welding speed with local heating. In the welding process, particularly for e-mobility applications, the demand for quality control via all-point inspection is increasing. The laser process enables real-time observation of the welding area during processing, making all-point inspection possible. In this study, we investigated the possibility of predicting weld bead width from a set of images acquired using a CMOS camera with a band-pass filter. Machine learning was used for the prediction, and the prediction accuracy was determined using the Root Mean Squared Error (RMSE). The laser parameters, such as irradiation power and scan speed, and 13 feature values, such as the area, centroid, and rotation angle of the light emission acquired from the images and were used as training data. The RMSE of 0.16 mm was achieved for a bead width of 0.5-1.5 mm, confirming that the prediction was sufficiently accurate. Furthermore, we conducted an analysis with and without spectroscopic images to verify whether spectroscopic images are effective for the evaluation of laser welding using machine learning.
In nanosecond pulsed laser processing techniques such as laser annealing and laser doping, the surface temperature of the laser-irradiated area changes on a nanosecond scale, which strongly affects properties of the processed material. Therefore, a temperature measurement method with in-situ, non-contact, nanosecond time response and microscalespatial resolution is necessary to optimize the laser processing conditions. In this study, a two-dimensional temperature distribution on a Si wafer surface irradiated by a nanosecond pulsed laser was estimated by a two-color temperature method using an ICCD camera with nanosecond time resolution. 20 ns after the laser irradiation at 1.0 J/cm2, the area above 1500 K started to appear in the two-dimensional temperature distribution. It is confirmed that the high temperature area increased further at 40 ns and was maintained for a certain period of time in temperature distribution. The average temperature at the center of the laser-irradiated area reached above 1685 K, which is the melting point of Si, at 40 ns and remained until 110 ns. The probe laser was irradiated to the laser irradiated area and the reflectivity was measured. The reflectivity varied according to the change between the solid and liquid phases on the Si surface, and the results corresponded to the two-dimensional temperature distribution.
4H–Silicon carbide (4H-SiC), which is a wide-bandgap semiconductor, is a promising material for high-power, ecofriendly devices owing to its excellent material properties. For the fabrication of SiC power devices, low-resistance ohmic contact must be established at the metal–semiconductor interface, which requires high-concentration impurity doping. In this study, we successfully doped 4H-SiC with high-concentration nitrogen under excimer laser irradiation using SiNx films containing dopants on 4H-SiC. Results indicated that a contact resistance of 10−6 Ωcm2 was obtained. The effects of doping characteristics due to different laser parameters were also investigated.
SiO2 nanoporous films has been attracting attention as low-k dielectric constant insulating films. We have succeeded in SiO2 nanoparticles with a particle size of a few nm and depositing a nanoporous film by pulsed laser deposition with controlling the ambient gas pressure. However, the details of the formation process of SiO2 nanoparticles have not been clarified. In this study, we visualized the time-resolved nanoparticle distribution in the gas phase by laser imaging technique to clarify the nanoparticle formation process and to be helpful for optimizing the growth condition of the low-k nanoporous film.
The crystallization of a-Si leads to alterations in the morphology of Si film such as surface color and surface roughness as a result of excimer laser annealing (ELA). These surface changes correlate with the characteristics of polysilicon films. The quality of crystallized poly Si has been evaluated by Non-destructive optical inspection methods. This study aims to use deep learning to estimate the quantitative relationship between the microscope images of a low-temperature polycrystalline silicon (LTPS) film and the mobility of an LTPS thin film transistor (TFT). This method would make it possible to measure the mobility from the images captured after annealing and improve the crystallization by in situ feedback. An a-Si substrate with a film thickness of 100 nm was polycrystallized by employing a KrF (wavelength of 248 nm) excimer laser, after which an optical microscope image of the substrate was captured. By changing the laser fluence and the number of shots (44 conditions N=10), LTPS films of various surface morphology were fabricated. We fabricated 440 transistors using these LTPS channels (channel size L = 20 μm, W = 30 μm) and measured their mobilities. Then, we performed deep learning with these sets of annealed optical microscope images and the corresponding mobilities. The mobility was estimated with an accuracy of ±12.8 cm2 V-1 s-1. Further improvement of the prediction accuracy (<±5 %) is needed for in-situ feedback. We plan to increase the number of images and use transfer learning to improve prediction accuracy.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.